Canny edge detector is the most popular tool for edge detection and has many applications in the areas of image processing, multimedia and computer vision. The Canny algorithm optimizes the edge detection through noise filtering using an optimal function approximated by the first derivative of a Gaussian. It identifies the edge points by computing the gradients of light intensity function based on the fact that the edge points likely appear where the gradient magnitudes are large. Hexagonal structure is an image structure alternative to traditional square image structure. Because all the existing hardware for capturing image and for displaying image are produced based on square structure, an approach that uses linear interpolation described for conversion between square and hexagonal structures. Gaussian filtering together with gradient computation is performed on the hexagonal structure. The pixel edge strengths on the square structure are then estimated before the thresholds of Canny algorithm are applied to determine the final edge map. The experimental results show the edge detection on hexagonal structure using static and video images, and the comparison with the results using Canny algorithm on square structure.

en_US

dc.publisher

IEEE

en_US

dc.relation.ispartof

2009 Joint Conferences on Pervasive Computing (JCPC2009)

en_US

dc.relation.isbasedon

10.1109/JCPC.2009.5420196

en_US

dc.title

Canny edge detection on a virtual hexagonal image structure

en_US

dc.type

Conference Proceeding

utslib.location

Taipei, Taiwan

en_US

utslib.location.activity

Taipei, Taiwan

en_US

utslib.for

080106 Image Processing

en_US

utslib.for

080104 Computer Vision

en_US

utslib.for

080109 Pattern Recognition and Data Mining

en_US

dc.location.activity

Taipei, Taiwan

en_US

dc.location.activity

Taipei, Taiwan

dc.location.activity

Taipei, Taiwan

pubs.embargo.period

Not known

en_US

pubs.organisational-group

/University of Technology Sydney

pubs.organisational-group

/University of Technology Sydney/Faculty of Engineering and Information Technology

pubs.organisational-group

/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computing and Communications

Canny edge detector is the most popular tool for edge detection and has many applications in the areas of image processing, multimedia and computer vision. The Canny algorithm optimizes the edge detection through noise filtering using an optimal function approximated by the first derivative of a Gaussian. It identifies the edge points by computing the gradients of light intensity function based on the fact that the edge points likely appear where the gradient magnitudes are large. Hexagonal structure is an image structure alternative to traditional square image structure. Because all the existing hardware for capturing image and for displaying image are produced based on square structure, an approach that uses linear interpolation described for conversion between square and hexagonal structures. Gaussian filtering together with gradient computation is performed on the hexagonal structure. The pixel edge strengths on the square structure are then estimated before the thresholds of Canny algorithm are applied to determine the final edge map. The experimental results show the edge detection on hexagonal structure using static and video images, and the comparison with the results using Canny algorithm on square structure.

OPUS Help

OPUS

OPUS (Open Publications of UTS Scholars) is the UTS institutional repository. It showcases the research of UTS staff and postgraduate students to a global audience. For you, as a researcher, OPUS increases the visibility and accessibility of your research by making it openly available regardless of where you choose to publish.

Items in OPUS are enhanced with high quality metadata and seeded to search engines such as Google Scholar as well as being linked to your UTS research profile, increasing discoverability and opportunities for citation of your work and collaboration. In addition, works in OPUS are preserved for long-term access and discovery.

The UTS Open Access Policy requires UTS research outputs to be openly available via OPUS. Depositing your work in OPUS also assists you in complying with ARC, NHMRC and other funder Open Access policies. Providing Open Access to your research outputs through OPUS not only ensures you comply with these important policies, but increases opportunities for other researchers to cite and build upon your work.

OPUS archives UTS research submitted for Higher Education Research Data Collection (HERDC) and Excellence in Research for Australia (ERA). It also stores digital theses and forms of scholarship that do not usually see formal publication.

How can you deposit works in OPUS?

When you claim (or enter) your research in Symplectic Elements, simply upload a copy of your work which can be made openly available. Symplectic provides information on which version of your work to upload. If you are unsure, please supply a copy of the Accepted Manuscript version. Ensure you check the box to "agree to the OPUS license terms".

Once uploaded, your works are automatically sent to OPUS and placed temporarily in Closed Access until reviewed by UTS Library staff.